Indicações do manejo de pragas para percevejos.

Epocas de aparecimento; Determinacao da intensidade populacional; Metodos de amostragem; Ocorrencia nas diferentes cultivares; Controle; Biologia; Consideracoes finais.bitstream/item/23229/1/Doc9.pd

Recomendações de inseticidas para utilização no programa de manejo de pragas da soja - safra 1981/82 - nos Estados do Paraná, São Paulo e Mato Grosso do Sul.

bitstream/item/53974/1/11.pd

Recomendacoes de inseticidas para utilizacao no Programa de Manejo de Pragas da Soja safra 1982/83 nos Estados de Mato Grosso do Sul, Parana e Sao Paulo.

bitstream/item/53973/1/17.pd

Mean clustering coefficients: the role of isolated nodes and leafs on clustering measures for small-world networks

Many networks exhibit the small-world property of the neighborhood connectivity being higher than in comparable random networks. However, the standard measure of local neighborhood clustering is typically not defined if a node has one or no neighbors. In such cases, local clustering has traditionally been set to zero and this value influenced the global clustering coefficient. Such a procedure leads to underestimation of the neighborhood clustering in sparse networks. We propose to include $\theta$ as the proportion of leafs and isolated nodes to estimate the contribution of these cases and provide a formula for estimating a clustering coefficient excluding these cases from the Watts and Strogatz (1998 Nature 393 440-2) definition of the clustering coefficient. Excluding leafs and isolated nodes leads to values which are up to 140% higher than the traditional values for the observed networks indicating that neighborhood connectivity is normally underestimated. We find that the definition of the clustering coefficient has a major effect when comparing different networks. For metabolic networks of 43 organisms, relations changed for 58% of the comparisons when a different definition was applied. We also show that the definition influences small-world features and that the classification can change from non-small-world to small-world network. We discuss the use of an alternative measure, disconnectedness D, which is less influenced by leafs and isolated nodes.Comment: final version of the manuscrip